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2018 | OriginalPaper | Chapter

Exploiting OSC Models by Using Neural Networks with an Innovative Pruning Algorithm

Authors : Grazia Lo Sciuto, Giacomo Capizzi, Christian Napoli, Rafi Shikler, Dawid Połap, Marcin Woźniak

Published in: Artificial Intelligence and Soft Computing

Publisher: Springer International Publishing

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Abstract

In this paper we have investigated the relationship between the current and the active layer thickness of an organic solar cell (OSC) in order to improve its efficiency by means of a back propagation neural network. In order to preserve the generalization properties of the adopted neural network (NN) in this paper is presented also an innovative pruning technique. The extensive simulations performed show a good agreement between simulated and experimental data with an overall error of about 3%. The obtained results demostrate that the use of an MLP with associated an appropriate pruning algorithm to preserve its generalization capacities permits to accurately reproduce the relationship between the active layer thicknesses and the measured maximum power in an OSC. This neural model can be of great use in manufacturing processes.

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Title: Exploiting OSC Models by Using Neural Networks with an Innovative Pruning Algorithm
Authors: Grazia Lo Sciuto
Giacomo Capizzi
Christian Napoli
Rafi Shikler
Dawid Połap
Marcin Woźniak
Publisher: Springer International Publishing
Book: Artificial Intelligence and Soft Computing
Print ISBN: 978-3-319-91261-5

Electronic ISBN: 978-3-319-91262-2

Copyright Year: 2018
DOI: https://doi.org/10.1007/978-3-319-91262-2_62

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